Overview

Brought to you by YData

Dataset statistics

Number of variables18
Number of observations10,000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory123.0 B

Variable types

Numeric15
Boolean3

Alerts

studio has constant value "False" Constant
build_year is highly overall correlated with building_id and 2 other fieldsHigh correlation
building_id is highly overall correlated with build_year and 2 other fieldsHigh correlation
building_type is highly overall correlated with ceiling_heightHigh correlation
ceiling_height is highly overall correlated with building_typeHigh correlation
floor is highly overall correlated with floors_totalHigh correlation
floors_total is highly overall correlated with build_year and 2 other fieldsHigh correlation
has_elevator is highly overall correlated with build_year and 1 other fieldsHigh correlation
living_area is highly overall correlated with price and 2 other fieldsHigh correlation
price is highly overall correlated with living_area and 2 other fieldsHigh correlation
rooms is highly overall correlated with living_area and 2 other fieldsHigh correlation
total_area is highly overall correlated with living_area and 2 other fieldsHigh correlation
is_apartment is highly imbalanced (91.9%) Imbalance
has_elevator is highly imbalanced (53.0%) Imbalance
price is highly skewed (γ1 = 34.64963142) Skewed
id is uniformly distributed Uniform
id has unique values Unique
kitchen_area has 730 (7.3%) zeros Zeros
living_area has 629 (6.3%) zeros Zeros
building_type has 123 (1.2%) zeros Zeros

Reproduction

Analysis started2025-05-13 13:40:07.927107
Analysis finished2025-05-13 13:41:04.021505
Duration56.09 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

id
Real number (ℝ)

Uniform  Unique 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4999.5
Minimum0
Maximum9999
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:04.293504image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile499.95
Q12499.75
median4999.5
Q37499.25
95-th percentile9499.05
Maximum9999
Range9999
Interquartile range (IQR)4999.5

Descriptive statistics

Standard deviation2886.8957
Coefficient of variation (CV)0.57743688
Kurtosis-1.2
Mean4999.5
Median Absolute Deviation (MAD)2500
Skewness0
Sum49995000
Variance8334166.7
MonotonicityStrictly increasing
2025-05-13T16:41:04.778101image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9999 1
 
< 0.1%
0 1
 
< 0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
0 1
< 0.1%
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
ValueCountFrequency (%)
9999 1
< 0.1%
9998 1
< 0.1%
9997 1
< 0.1%
9996 1
< 0.1%
9995 1
< 0.1%
9994 1
< 0.1%
9993 1
< 0.1%
9992 1
< 0.1%
9991 1
< 0.1%
9990 1
< 0.1%

floor
Real number (ℝ)

High correlation 

Distinct47
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3318
Minimum1
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:05.257463image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q310
95-th percentile17
Maximum49
Range48
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.5705307
Coefficient of variation (CV)0.75977668
Kurtosis5.1072479
Mean7.3318
Median Absolute Deviation (MAD)3
Skewness1.6792073
Sum73318
Variance31.030812
MonotonicityNot monotonic
2025-05-13T16:41:05.756366image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
2 1033
10.3%
3 990
9.9%
5 954
9.5%
4 931
 
9.3%
1 791
 
7.9%
7 687
 
6.9%
6 667
 
6.7%
9 604
 
6.0%
8 593
 
5.9%
10 413
 
4.1%
Other values (37) 2337
23.4%
ValueCountFrequency (%)
1 791
7.9%
2 1033
10.3%
3 990
9.9%
4 931
9.3%
5 954
9.5%
6 667
6.7%
7 687
6.9%
8 593
5.9%
9 604
6.0%
10 413
 
4.1%
ValueCountFrequency (%)
49 1
 
< 0.1%
48 1
 
< 0.1%
46 4
< 0.1%
45 2
< 0.1%
44 3
< 0.1%
43 1
 
< 0.1%
42 3
< 0.1%
41 1
 
< 0.1%
40 1
 
< 0.1%
39 2
< 0.1%

is_apartment
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9899 
True
 
101
ValueCountFrequency (%)
False 9899
99.0%
True 101
 
1.0%
2025-05-13T16:41:06.159964image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

kitchen_area
Real number (ℝ)

Zeros 

Distinct342
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.767798
Minimum0
Maximum100
Zeros730
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:06.450544image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.1799998
median8.6000004
Q310
95-th percentile16
Maximum100
Range100
Interquartile range (IQR)3.8200002

Descriptive statistics

Standard deviation4.7654227
Coefficient of variation (CV)0.5435142
Kurtosis26.100833
Mean8.767798
Median Absolute Deviation (MAD)1.8999996
Skewness2.6868581
Sum87677.98
Variance22.709254
MonotonicityNot monotonic
2025-05-13T16:41:06.691461image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 1128
 
11.3%
10 914
 
9.1%
0 730
 
7.3%
9 701
 
7.0%
8 520
 
5.2%
7 406
 
4.1%
12 285
 
2.9%
11 239
 
2.4%
8.5 220
 
2.2%
6.5 161
 
1.6%
Other values (332) 4696
47.0%
ValueCountFrequency (%)
0 730
7.3%
2 2
 
< 0.1%
2.099999905 1
 
< 0.1%
3 19
 
0.2%
3.200000048 1
 
< 0.1%
3.5 3
 
< 0.1%
4 18
 
0.2%
4.099999905 1
 
< 0.1%
4.400000095 1
 
< 0.1%
4.5 2
 
< 0.1%
ValueCountFrequency (%)
100 1
 
< 0.1%
60 2
< 0.1%
59 1
 
< 0.1%
57 1
 
< 0.1%
51 1
 
< 0.1%
50 3
< 0.1%
45 1
 
< 0.1%
43.79999924 1
 
< 0.1%
41 1
 
< 0.1%
40 3
< 0.1%

living_area
Real number (ℝ)

High correlation  Zeros 

Distinct851
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.316953
Minimum0
Maximum700
Zeros629
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:07.505663image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119.5
median30
Q341.400002
95-th percentile64.599999
Maximum700
Range700
Interquartile range (IQR)21.900002

Descriptive statistics

Standard deviation21.933199
Coefficient of variation (CV)0.67869019
Kurtosis99.19366
Mean32.316953
Median Absolute Deviation (MAD)10.700001
Skewness5.2156838
Sum323169.53
Variance481.06523
MonotonicityNot monotonic
2025-05-13T16:41:08.046334image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 629
 
6.3%
19 462
 
4.6%
20 338
 
3.4%
30 280
 
2.8%
18 275
 
2.8%
32 242
 
2.4%
18.89999962 176
 
1.8%
28 162
 
1.6%
31 156
 
1.6%
45 148
 
1.5%
Other values (841) 7132
71.3%
ValueCountFrequency (%)
0 629
6.3%
8.600000381 3
 
< 0.1%
8.899999619 1
 
< 0.1%
9 1
 
< 0.1%
10 9
 
0.1%
10.10000038 4
 
< 0.1%
10.19999981 1
 
< 0.1%
10.80000019 1
 
< 0.1%
11 3
 
< 0.1%
11.30000019 1
 
< 0.1%
ValueCountFrequency (%)
700 1
 
< 0.1%
278 1
 
< 0.1%
247 1
 
< 0.1%
245.8999939 1
 
< 0.1%
230 2
< 0.1%
216 1
 
< 0.1%
213 1
 
< 0.1%
210 2
< 0.1%
206.8000031 1
 
< 0.1%
200 3
< 0.1%

rooms
Real number (ℝ)

High correlation 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0628
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:08.441084image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.94262666
Coefficient of variation (CV)0.45696464
Kurtosis1.3111541
Mean2.0628
Median Absolute Deviation (MAD)1
Skewness0.82784522
Sum20628
Variance0.88854501
MonotonicityNot monotonic
2025-05-13T16:41:08.625742image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 3822
38.2%
1 3151
31.5%
3 2458
24.6%
4 432
 
4.3%
5 101
 
1.0%
6 29
 
0.3%
7 6
 
0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
1 3151
31.5%
2 3822
38.2%
3 2458
24.6%
4 432
 
4.3%
5 101
 
1.0%
6 29
 
0.3%
7 6
 
0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
7 6
 
0.1%
6 29
 
0.3%
5 101
 
1.0%
4 432
 
4.3%
3 2458
24.6%
2 3822
38.2%
1 3151
31.5%

studio
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-05-13T16:41:08.777337image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

total_area
Real number (ℝ)

High correlation 

Distinct1184
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.636976
Minimum12.3
Maximum901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:09.005051image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum12.3
5-th percentile32.099998
Q138.900002
median51.599998
Q366
95-th percentile109.41
Maximum901
Range888.7
Interquartile range (IQR)27.099998

Descriptive statistics

Standard deviation33.941564
Coefficient of variation (CV)0.57884233
Kurtosis81.079835
Mean58.636976
Median Absolute Deviation (MAD)13.099998
Skewness5.9460219
Sum586369.76
Variance1152.0298
MonotonicityNot monotonic
2025-05-13T16:41:09.228462image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38 255
 
2.5%
45 217
 
2.2%
52 164
 
1.6%
39 162
 
1.6%
60 161
 
1.6%
40 150
 
1.5%
54 129
 
1.3%
35 128
 
1.3%
33 127
 
1.3%
44 104
 
1.0%
Other values (1174) 8403
84.0%
ValueCountFrequency (%)
12.30000019 1
< 0.1%
13.30000019 1
< 0.1%
15.14999962 1
< 0.1%
15.80000019 1
< 0.1%
15.89999962 1
< 0.1%
16 1
< 0.1%
16.10000038 1
< 0.1%
16.44000053 1
< 0.1%
16.79999924 1
< 0.1%
17.20000076 1
< 0.1%
ValueCountFrequency (%)
901 1
< 0.1%
757.7999878 1
< 0.1%
508 1
< 0.1%
494 1
< 0.1%
492.2999878 1
< 0.1%
486 1
< 0.1%
454 1
< 0.1%
400 1
< 0.1%
380 1
< 0.1%
376 1
< 0.1%

price
Real number (ℝ)

High correlation  Skewed 

Distinct1392
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16901277
Minimum11200
Maximum2.4295601 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:09.624101image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum11200
5-th percentile6500000
Q18850000
median11500000
Q315800000
95-th percentile38000000
Maximum2.4295601 × 109
Range2.4295489 × 109
Interquartile range (IQR)6950000

Descriptive statistics

Standard deviation36452151
Coefficient of variation (CV)2.156769
Kurtosis2003.1141
Mean16901277
Median Absolute Deviation (MAD)3100000
Skewness34.649631
Sum1.6901277 × 1011
Variance1.3287593 × 1015
MonotonicityNot monotonic
2025-05-13T16:41:10.133914image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10500000 177
 
1.8%
9500000 175
 
1.8%
12500000 155
 
1.6%
11000000 142
 
1.4%
12000000 138
 
1.4%
8500000 137
 
1.4%
11500000 130
 
1.3%
9000000 117
 
1.2%
13500000 109
 
1.1%
10000000 106
 
1.1%
Other values (1382) 8614
86.1%
ValueCountFrequency (%)
11200 1
< 0.1%
27000 2
< 0.1%
1799900 1
< 0.1%
2500000 1
< 0.1%
2550000 2
< 0.1%
3000000 1
< 0.1%
3290000 1
< 0.1%
3329999 1
< 0.1%
3330000 1
< 0.1%
3350000 1
< 0.1%
ValueCountFrequency (%)
2429560064 1
< 0.1%
766955008 1
< 0.1%
727922944 1
< 0.1%
720000000 1
< 0.1%
707742016 1
< 0.1%
632951872 1
< 0.1%
539396992 1
< 0.1%
459397216 1
< 0.1%
443337600 1
< 0.1%
418455008 1
< 0.1%

building_id
Real number (ℝ)

High correlation 

Distinct7008
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13626.979
Minimum3
Maximum24618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:10.665091image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile2057.85
Q18414.75
median13665.5
Q319528.25
95-th percentile23838
Maximum24618
Range24615
Interquartile range (IQR)11113.5

Descriptive statistics

Standard deviation6785.487
Coefficient of variation (CV)0.49794506
Kurtosis-1.0420645
Mean13626.979
Median Absolute Deviation (MAD)5572
Skewness-0.13269277
Sum1.3626979 × 108
Variance46042834
MonotonicityNot monotonic
2025-05-13T16:41:11.191355image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24195 43
 
0.4%
24118 13
 
0.1%
24225 11
 
0.1%
24327 10
 
0.1%
24035 10
 
0.1%
17272 9
 
0.1%
24208 9
 
0.1%
22965 8
 
0.1%
23136 8
 
0.1%
23137 8
 
0.1%
Other values (6998) 9871
98.7%
ValueCountFrequency (%)
3 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
15 1
 
< 0.1%
16 3
< 0.1%
25 1
 
< 0.1%
27 2
< 0.1%
33 1
 
< 0.1%
42 1
 
< 0.1%
ValueCountFrequency (%)
24618 1
 
< 0.1%
24615 1
 
< 0.1%
24610 2
< 0.1%
24603 1
 
< 0.1%
24602 2
< 0.1%
24600 1
 
< 0.1%
24593 3
< 0.1%
24584 1
 
< 0.1%
24580 1
 
< 0.1%
24575 2
< 0.1%

build_year
Real number (ℝ)

High correlation 

Distinct112
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1985.2416
Minimum1901
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:11.678501image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1901
5-th percentile1957
Q11969
median1982
Q32005
95-th percentile2017
Maximum2023
Range122
Interquartile range (IQR)36

Descriptive statistics

Standard deviation21.420292
Coefficient of variation (CV)0.010789766
Kurtosis-0.077791035
Mean1985.2416
Median Absolute Deviation (MAD)17
Skewness-0.29398646
Sum19852416
Variance458.82891
MonotonicityNot monotonic
2025-05-13T16:41:12.189342image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2018 266
 
2.7%
1968 261
 
2.6%
1970 253
 
2.5%
1972 246
 
2.5%
1969 239
 
2.4%
1967 237
 
2.4%
1971 234
 
2.3%
2017 223
 
2.2%
1973 222
 
2.2%
1975 222
 
2.2%
Other values (102) 7597
76.0%
ValueCountFrequency (%)
1901 1
 
< 0.1%
1902 7
0.1%
1903 3
 
< 0.1%
1904 1
 
< 0.1%
1905 6
0.1%
1906 2
 
< 0.1%
1907 2
 
< 0.1%
1908 3
 
< 0.1%
1910 8
0.1%
1911 4
< 0.1%
ValueCountFrequency (%)
2023 1
 
< 0.1%
2022 7
 
0.1%
2021 5
 
0.1%
2020 36
 
0.4%
2019 70
 
0.7%
2018 266
2.7%
2017 223
2.2%
2016 176
1.8%
2015 212
2.1%
2014 171
1.7%

building_type
Real number (ℝ)

High correlation  Zeros 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3015
Minimum0
Maximum6
Zeros123
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:12.578007image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q34
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4606886
Coefficient of variation (CV)0.4424318
Kurtosis-0.59894326
Mean3.3015
Median Absolute Deviation (MAD)0
Skewness-0.34862082
Sum33015
Variance2.1336111
MonotonicityNot monotonic
2025-05-13T16:41:12.982259image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4 5861
58.6%
1 1695
 
17.0%
2 1439
 
14.4%
6 784
 
7.8%
0 123
 
1.2%
3 98
 
1.0%
ValueCountFrequency (%)
0 123
 
1.2%
1 1695
 
17.0%
2 1439
 
14.4%
3 98
 
1.0%
4 5861
58.6%
6 784
 
7.8%
ValueCountFrequency (%)
6 784
 
7.8%
4 5861
58.6%
3 98
 
1.0%
2 1439
 
14.4%
1 1695
 
17.0%
0 123
 
1.2%

latitude
Real number (ℝ)

Distinct6268
Distinct (%)62.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.735827
Minimum55.419483
Maximum56.011032
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:13.359846image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum55.419483
5-th percentile55.5695
Q155.65591
median55.73558
Q355.815793
95-th percentile55.887362
Maximum56.011032
Range0.59154892
Interquartile range (IQR)0.1598835

Descriptive statistics

Standard deviation0.10402574
Coefficient of variation (CV)0.001866407
Kurtosis-0.55800337
Mean55.735827
Median Absolute Deviation (MAD)0.080015182
Skewness0.0067565275
Sum557358.27
Variance0.010821354
MonotonicityNot monotonic
2025-05-13T16:41:13.875720image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55.77080536 44
 
0.4%
55.78516769 21
 
0.2%
55.78421021 19
 
0.2%
55.83442688 17
 
0.2%
55.63152313 14
 
0.1%
55.83548737 13
 
0.1%
55.74351883 11
 
0.1%
55.80357361 11
 
0.1%
55.55776596 11
 
0.1%
55.69853592 10
 
0.1%
Other values (6258) 9829
98.3%
ValueCountFrequency (%)
55.41948318 1
< 0.1%
55.43046188 1
< 0.1%
55.43102264 2
< 0.1%
55.43135452 2
< 0.1%
55.4327507 1
< 0.1%
55.4480896 1
< 0.1%
55.46511078 1
< 0.1%
55.46642685 1
< 0.1%
55.46683502 1
< 0.1%
55.46781921 1
< 0.1%
ValueCountFrequency (%)
56.0110321 1
< 0.1%
56.00934601 2
< 0.1%
56.00914001 1
< 0.1%
56.00882339 1
< 0.1%
56.00812149 2
< 0.1%
56.00650787 1
< 0.1%
56.00598526 2
< 0.1%
56.00557709 1
< 0.1%
56.00255966 2
< 0.1%
56.00019836 1
< 0.1%

longitude
Real number (ℝ)

Distinct6201
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.591939
Minimum36.864372
Maximum37.941315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:14.960155image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum36.864372
5-th percentile37.351322
Q137.493991
median37.587103
Q337.703157
95-th percentile37.828638
Maximum37.941315
Range1.0769424
Interquartile range (IQR)0.20916653

Descriptive statistics

Standard deviation0.15228009
Coefficient of variation (CV)0.0040508709
Kurtosis0.35146517
Mean37.591939
Median Absolute Deviation (MAD)0.097723007
Skewness-0.21956036
Sum375919.39
Variance0.023189226
MonotonicityNot monotonic
2025-05-13T16:41:15.536180image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5642128 46
 
0.5%
37.56404114 22
 
0.2%
37.56266785 20
 
0.2%
37.65960312 18
 
0.2%
37.65834808 15
 
0.1%
37.5163765 14
 
0.1%
37.42210007 11
 
0.1%
37.55502319 11
 
0.1%
37.59103775 11
 
0.1%
37.93551636 10
 
0.1%
Other values (6191) 9822
98.2%
ValueCountFrequency (%)
36.86437225 1
 
< 0.1%
36.86503601 2
< 0.1%
36.86582565 2
< 0.1%
36.86939239 1
 
< 0.1%
36.92002106 2
< 0.1%
37.14593124 3
< 0.1%
37.14622498 1
 
< 0.1%
37.14664841 1
 
< 0.1%
37.14690781 1
 
< 0.1%
37.14756393 2
< 0.1%
ValueCountFrequency (%)
37.9413147 4
< 0.1%
37.94085693 3
< 0.1%
37.93956375 5
0.1%
37.93946457 1
 
< 0.1%
37.9389267 2
 
< 0.1%
37.93870926 5
0.1%
37.9375267 3
< 0.1%
37.93703842 1
 
< 0.1%
37.93697739 2
 
< 0.1%
37.93670654 4
< 0.1%

ceiling_height
Real number (ℝ)

High correlation 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7356491
Minimum2
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:16.100427image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.48
Q12.6400001
median2.6400001
Q32.8
95-th percentile3.0999999
Maximum8
Range6
Interquartile range (IQR)0.15999985

Descriptive statistics

Standard deviation0.21147813
Coefficient of variation (CV)0.077304556
Kurtosis86.70175
Mean2.7356491
Median Absolute Deviation (MAD)0.059999943
Skewness4.9562346
Sum27356.491
Variance0.044723001
MonotonicityNot monotonic
2025-05-13T16:41:16.625299image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
2.640000105 4461
44.6%
3 1464
 
14.6%
2.700000048 1102
 
11.0%
2.480000019 623
 
6.2%
2.74000001 493
 
4.9%
2.799999952 454
 
4.5%
2.5 279
 
2.8%
3.200000048 235
 
2.4%
2.599999905 158
 
1.6%
2.75 147
 
1.5%
Other values (38) 584
 
5.8%
ValueCountFrequency (%)
2 2
 
< 0.1%
2.400000095 2
 
< 0.1%
2.480000019 623
6.2%
2.5 279
2.8%
2.529999971 1
 
< 0.1%
2.539999962 4
 
< 0.1%
2.549999952 3
 
< 0.1%
2.569999933 1
 
< 0.1%
2.599999905 158
 
1.6%
2.630000114 2
 
< 0.1%
ValueCountFrequency (%)
8 2
 
< 0.1%
6 1
 
< 0.1%
4.5 1
 
< 0.1%
4.190000057 2
 
< 0.1%
4.150000095 7
0.1%
4.099999905 1
 
< 0.1%
4 13
0.1%
3.910000086 2
 
< 0.1%
3.799999952 4
 
< 0.1%
3.75 1
 
< 0.1%

flats_count
Real number (ℝ)

Distinct668
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean245.4229
Minimum1
Maximum1630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:16.857442image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile60
Q1111
median196
Q3320
95-th percentile586
Maximum1630
Range1629
Interquartile range (IQR)209

Descriptive statistics

Standard deviation199.08681
Coefficient of variation (CV)0.81119901
Kurtosis13.444195
Mean245.4229
Median Absolute Deviation (MAD)96
Skewness2.7930255
Sum2454229
Variance39635.559
MonotonicityNot monotonic
2025-05-13T16:41:17.218215image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 267
 
2.7%
84 216
 
2.2%
144 205
 
2.1%
215 187
 
1.9%
72 183
 
1.8%
287 152
 
1.5%
60 151
 
1.5%
128 141
 
1.4%
98 135
 
1.4%
320 132
 
1.3%
Other values (658) 8231
82.3%
ValueCountFrequency (%)
1 15
0.1%
2 10
0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 4
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
1630 44
0.4%
1623 11
 
0.1%
1586 2
 
< 0.1%
1198 4
 
< 0.1%
1183 3
 
< 0.1%
1133 1
 
< 0.1%
1114 2
 
< 0.1%
1112 6
 
0.1%
1057 5
 
0.1%
1056 4
 
< 0.1%

floors_total
Real number (ℝ)

High correlation 

Distinct50
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.8451
Minimum2
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.2 KiB
2025-05-13T16:41:17.566836image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q19
median14
Q317
95-th percentile25
Maximum99
Range97
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.6606413
Coefficient of variation (CV)0.48108293
Kurtosis7.6704682
Mean13.8451
Median Absolute Deviation (MAD)4
Skewness1.6956144
Sum138451
Variance44.364142
MonotonicityNot monotonic
2025-05-13T16:41:17.807539image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 1865
18.6%
17 1717
17.2%
12 1272
12.7%
5 931
9.3%
14 822
8.2%
16 783
7.8%
22 393
 
3.9%
8 288
 
2.9%
25 286
 
2.9%
10 181
 
1.8%
Other values (40) 1462
14.6%
ValueCountFrequency (%)
2 4
 
< 0.1%
3 31
 
0.3%
4 56
 
0.6%
5 931
9.3%
6 105
 
1.1%
7 125
 
1.2%
8 288
 
2.9%
9 1865
18.6%
10 181
 
1.8%
11 66
 
0.7%
ValueCountFrequency (%)
99 1
 
< 0.1%
58 4
 
< 0.1%
57 1
 
< 0.1%
56 8
 
0.1%
49 2
 
< 0.1%
48 2
 
< 0.1%
47 15
 
0.1%
46 2
 
< 0.1%
44 46
0.5%
43 3
 
< 0.1%

has_elevator
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
8997 
False
1003 
ValueCountFrequency (%)
True 8997
90.0%
False 1003
 
10.0%
2025-05-13T16:41:17.987386image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Interactions

2025-05-13T16:40:58.482935image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:08.717705image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:12.308482image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:15.255533image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:18.009692image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:20.657310image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:24.348003image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:28.741944image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:34.174780image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:39.767475image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:43.185486image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:45.982966image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:48.723315image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:51.508850image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:54.918766image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:58.661984image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:08.900621image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:12.785245image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:15.445613image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:18.181207image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:20.810286image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:24.501966image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:29.105603image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:34.533261image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:40.089472image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:43.347695image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:46.143478image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:48.881395image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:51.684434image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:55.272213image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:58.823478image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:09.300742image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:12.938081image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:15.667399image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:18.361853image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:21.023943image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:24.656620image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:29.478503image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:34.862622image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:40.440385image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:43.515571image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:46.305461image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:49.038766image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:52.022573image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:55.549688image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:58.980764image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:09.629199image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:13.092718image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:15.935080image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:18.524379image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:21.304265image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:24.812665image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:29.847816image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:35.205003image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:40.775785image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:43.739231image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:46.536767image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:49.199313image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:52.287279image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:55.874548image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:59.155240image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:10.046683image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:13.303964image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:16.115240image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:18.696864image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:21.658322image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:25.099291image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:30.199552image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:35.587309image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:41.092129image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:43.932472image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:46.846771image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:49.377434image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:52.588215image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:56.232287image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:59.346390image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:10.396561image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:13.461733image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:16.270622image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:18.852328image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:21.916669image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:25.411752image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:30.573070image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:35.922078image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:41.414958image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:44.089738image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:47.008260image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:49.534597image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:52.857018image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:56.498235image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:59.507422image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:10.701360image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:13.615238image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:16.437141image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:19.077359image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:22.192287image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:25.750409image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:31.018901image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:36.282939image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:41.582347image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:44.247344image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:47.184130image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:49.686614image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:53.119480image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:56.660016image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:59.738568image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:10.868683image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:13.780746image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:16.626254image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:19.244951image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:22.449905image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:26.007908image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:31.332062image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:36.624304image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:41.753024image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:44.435030image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:47.351853image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:50.207296image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:53.363823image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:56.927777image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:59.998544image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:11.037930image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:13.941635image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:16.806608image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:19.409395image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:22.606306image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:26.338512image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:31.690217image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:36.945083image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:41.921948image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:44.616465image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:47.519776image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:50.359922image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:53.530842image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:57.097224image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:41:00.346508image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:11.239198image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:14.139137image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:16.990261image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:19.580327image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:22.770874image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:26.682171image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:32.034493image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:37.327174image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:42.092605image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:44.803812image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:47.692353image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:50.525048image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:53.702982image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:57.310751image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:41:00.704347image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:11.404193image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:14.299922image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:17.156246image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:19.753615image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:23.502267image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:27.024692image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:32.344004image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:37.622620image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:42.264590image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:44.996948image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:47.863081image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:50.691242image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:53.878457image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:57.493518image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:41:01.020208image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:11.572062image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:14.465415image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:17.319299image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:19.929833image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:23.669027image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:27.366580image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:32.663060image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:38.387824image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:42.444059image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:45.175362image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:48.036108image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:50.856435image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:54.044742image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:57.669921image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:41:01.346556image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:11.730060image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:14.615477image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:17.474790image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:20.136758image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:23.818652image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:27.693357image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:33.023336image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:38.724090image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:42.661018image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:45.332478image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:48.208366image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:51.006344image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:54.217441image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:57.830844image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:41:01.642049image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:11.903887image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:14.882078image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:17.637155image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:20.307757image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:23.979681image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:28.038235image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:33.377935image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:39.071072image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:42.839354image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:45.589814image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:48.376810image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:51.173832image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:54.397223image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:58.004850image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:41:02.007130image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:12.078057image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:15.091909image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:17.812187image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:20.492704image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:24.190356image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:28.402993image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:33.776481image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:39.444194image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:43.023667image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:45.810025image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:48.561395image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:51.348044image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:54.628589image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2025-05-13T16:40:58.215571image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Correlations

2025-05-13T16:41:18.127994image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
build_yearbuilding_idbuilding_typeceiling_heightflats_countfloorfloors_totalhas_elevatoridis_apartmentkitchen_arealatitudeliving_arealongitudepriceroomstotal_area
build_year1.0001.0000.0290.3220.4610.3920.7500.512-0.0050.1520.452-0.1870.015-0.2120.161-0.0150.249
building_id1.0001.0000.0390.3190.4600.3930.7510.579-0.0050.1460.452-0.1790.014-0.2110.159-0.0170.248
building_type0.0290.0391.000-0.5350.0960.0690.1460.373-0.0380.146-0.067-0.046-0.1350.083-0.332-0.163-0.259
ceiling_height0.3220.319-0.5351.0000.0470.1240.2020.2760.0250.0280.322-0.0380.185-0.0930.4450.1870.407
flats_count0.4610.4600.0960.0471.0000.2430.4760.347-0.0330.2060.141-0.147-0.003-0.0920.028-0.0260.088
floor0.3920.3930.0690.1240.2431.0000.5050.3260.0010.1700.241-0.0370.031-0.0940.142-0.0010.132
floors_total0.7500.7510.1460.2020.4760.5051.0000.406-0.0040.3050.450-0.0950.026-0.1790.182-0.0330.205
has_elevator0.5120.5790.3730.2760.3470.3260.4061.0000.0000.0200.1340.1840.0230.1140.0000.0500.037
id-0.005-0.005-0.0380.025-0.0330.001-0.0040.0001.0000.0450.0150.0350.0460.0270.0800.0500.046
is_apartment0.1520.1460.1460.0280.2060.1700.3050.0200.0451.0000.0980.0820.0980.0590.1070.1100.108
kitchen_area0.4520.452-0.0670.3220.1410.2410.4500.1340.0150.0981.000-0.1010.370-0.1460.3680.1690.422
latitude-0.187-0.179-0.046-0.038-0.147-0.037-0.0950.1840.0350.082-0.1011.0000.022-0.0210.0530.032-0.022
living_area0.0150.014-0.1350.185-0.0030.0310.0260.0230.0460.0980.3700.0221.000-0.0570.5910.7940.788
longitude-0.212-0.2110.083-0.093-0.092-0.094-0.1790.1140.0270.059-0.146-0.021-0.0571.000-0.171-0.040-0.110
price0.1610.159-0.3320.4450.0280.1420.1820.0000.0800.1070.3680.0530.591-0.1711.0000.6510.758
rooms-0.015-0.017-0.1630.187-0.026-0.001-0.0330.0500.0500.1100.1690.0320.794-0.0400.6511.0000.873
total_area0.2490.248-0.2590.4070.0880.1320.2050.0370.0460.1080.422-0.0220.788-0.1100.7580.8731.000

Missing values

2025-05-13T16:41:02.563349image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-13T16:41:03.601532image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

idflooris_apartmentkitchen_arealiving_arearoomsstudiototal_areapricebuilding_idbuild_yearbuilding_typelatitudelongitudeceiling_heightflats_countfloors_totalhas_elevator
009False9.9019.9000001False35.099998950000062201965655.71711337.7811202.648412True
117False0.0016.6000001False43.00000013500000180122001255.79484937.6080133.009710True
229False9.0032.0000002False56.00000013500000178212000455.74004037.7617422.708010True
331False10.1043.0999983False76.00000020000000185792002455.67201637.5708772.6477117True
443False3.0014.0000001False24.000000520000092931971155.80880737.7073062.602089True
559False0.000.0000002False51.0099988490104239642017455.72472837.7430692.7019217True
661False6.1829.3400002False44.520000950000055761964455.79558937.7226222.641805False
777False13.500.0000001False52.00000017990000230072015255.65634537.4243353.0051211True
887False8.1819.1000001False35.9199986300000134911982455.57473437.6686862.6412716True
995False8.0030.0000002False50.0000005900000137311982455.99469837.1966862.6414212True
idflooris_apartmentkitchen_arealiving_arearoomsstudiototal_areapricebuilding_idbuild_yearbuilding_typelatitudelongitudeceiling_heightflats_countfloors_totalhas_elevator
999099909False6.6045.0000003False62.79999913700000137231982455.90242437.5555992.5028712True
999199911False6.0034.0000002False50.0000001250000065251966455.71165137.7564162.641439True
999299929False10.0016.0000001False30.0000006999999229012015055.50416937.5390322.80119821True
999399938False8.6030.7999992False46.099998790000079501968655.66828937.6158562.648412True
999499942False8.1230.5000002False52.0000008100000154981990455.98907137.1482202.6422117True
999599957False12.0038.0000002False90.00000026000000167251997255.69855937.8449103.0034627True
999699965False9.0032.0000002False55.0000001224500037331961155.77828237.5176093.00485True
999799978False7.5019.0000001False38.0000005800000225152013455.70797737.9304392.7018317True
999899982False21.000.0000004False100.00000042000000238702017255.82241137.4320413.0074419True
999999996False10.2045.5999983False74.00000014000000146031986455.64712537.4059832.6413617True